Baoyu Imagine

Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate.

User Input Tools

When this skill prompts the user, follow this tool-selection rule (priority order):

1. Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.
2. Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
3. Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.

Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.

Script Directory

{baseDir} = this SKILL.md's directory. Main script: {baseDir}/scripts/main.ts. Resolve ${BUN_X}: prefer bun; else npx -y bun; else suggest brew install oven-sh/bun/bun.

Step 0: Load Preferences ⛔ BLOCKING

This step MUST complete before any image generation — generation is blocked until EXTEND.md exists.

Check these paths in order; first hit wins:

• Found → load, parse, apply. If default_model.[provider] is null → ask model only.
• Not found → run first-time setup (references/config/first-time-setup.md) using AskUserQuestion to collect provider + model + quality + save location. Save EXTEND.md, then continue. Do not generate images before this completes.

Legacy compatibility: if .baoyu-skills/baoyu-image-gen/EXTEND.md exists and the new path doesn't, the runtime renames it to baoyu-imagine. If both exist, the runtime leaves them alone and uses the new path.

EXTEND.md keys: default provider, default quality, default aspect ratio, default image size, OpenAI image API dialect, default models, batch worker cap, provider-specific batch limits. Schema: references/config/preferences-schema.md.

Usage

Minimum working examples — see references/usage-examples.md for the full set including per-provider invocations and batch mode.

Identity-preserving reference prompts

When the user wants a real person/character/object preserved from reference images, do not replace the reference with a long generic description. Prefer short, hard identity-preservation language:

• "Use the person/object in the reference image(s) as the same identity. Do not redesign it or create a similar-looking new subject."
• "Only change scene, clothing, pose, lighting, rendering style, and composition. Keep the face/proportions/hair/key accessories/overall identity from the references."
• If using multiple references, state that they are the same subject and should jointly define identity.

Pitfall: long descriptions like "young East Asian woman, oval face, clear eyes..." can cause the model to synthesize a new person matching the description instead of preserving the referenced person.

# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png

# With aspect ratio and high quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9 --quality 2k

# Prompt from files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png

# With reference image
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png

# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider dashscope --model qwen-image-2.0-pro

# OpenAI GPT Image 2
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai --model gpt-image-2

# Batch mode
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4

Reference-Image Identity Preservation

When the user wants a person/object preserved from reference images:

• Prefer a small curated set of existing source references (usually 2–4) over many images; large multi-megabyte refs can destabilize streaming providers.
• Make the prompt say the references are the same subject and the output must use that identity. Avoid long generic facial-feature descriptions that can cause the model to synthesize a new similar-looking person.
• Do not use newly generated outputs as references unless the user explicitly asks; generated refs compound drift.
• If results become too polished or influencer-like, reduce stylized refs and add explicit anti-beautification constraints (no face slimming, eye enlargement, heavy makeup, commercial travel shoot, over-smoothing).
• If the subject should look younger/older, preserve the face and express age through clothing, posture, scene, and styling; do not ask the model to change facial identity.

Options

Environment Variables

Load priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env

Codex/ChatGPT OAuth is not an OpenAI API key

--provider openai --model gpt-image-2 uses the standard OpenAI Images API (/v1/images/generations or /v1/images/edits) and requires OPENAI_API_KEY. A Codex or ChatGPT desktop login is a different entitlement and is not a drop-in replacement for OPENAI_API_KEY; do not paste a Codex OAuth token into OPENAI_API_KEY or only set OPENAI_BASE_URL to a Codex backend.

If the user wants to use their Codex subscription / GPT Image 2 entitlement without an OpenAI API key, route through a Codex-native backend instead of this skill's openai provider:

• In Codex runtime: use the native imagegen skill/tool.
• In non-Codex runtimes with codex CLI installed and logged in: use the repo-level scripts/codex-imagegen.sh wrapper when the calling skill supports it (for example baoyu-cover-image). Resolve it from the plugin/repo root and pass absolute prompt/output/reference paths.
• In Hermes runtimes with a native image_generate tool: use that tool as a fallback, and state whether reference images were passed directly or reconstructed from extracted traits.

Do not modify the existing openai provider to silently consume Codex OAuth. If first-class Codex OAuth support is added to baoyu-imagine, implement it as a distinct provider (for example openai-codex) with its own auth, route, request shape, docs, and tests. See references/codex-oauth-vs-openai-api-key.md.

Model Resolution

Priority (highest → lowest) applies to every provider:

1. CLI flag --model <id>
2. EXTEND.md default_model.[provider]
3. Env var <PROVIDER>_IMAGE_MODEL
4. Built-in default

For OpenAI, the built-in default is gpt-image-2. gpt-image-1.5, gpt-image-1, and GPT Image snapshots remain selectable with --model or OPENAI_IMAGE_MODEL.

For Azure, --model / default_model.azure is the Azure deployment name. AZURE_OPENAI_DEPLOYMENT is the preferred env var; AZURE_OPENAI_IMAGE_MODEL is kept as a backward-compatible alias. If your Azure deployment is named after the underlying model, use gpt-image-2; otherwise use the exact custom deployment name.

EXTEND.md overrides env vars: if EXTEND.md sets default_model.google: "gemini-3-pro-image-preview" and the env var sets GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview, EXTEND.md wins.

Display model info before each generation:

• Using [provider] / [model]
• Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL